Social profiling of electronic messages

ABSTRACT

A method of associating an electronic message social profile with electronic messages. The method comprises identifying a plurality of users having a social affinity to one another, tagging each of a plurality of electronic messages received at a plurality of messaging accounts of the plurality of users with at least one user behavior tag indicative of a behavioral messaging action performed by one of the plurality of users, identifying a cluster of electronic messages having a common content from the plurality of electronic messages according to a similarity analysis, calculating, using a processor, an electronic message social profile for members of the cluster based on a combination of respective the at least one user behavior tag of the members of the cluster, and associating the electronic message social profile with the members of the cluster.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/469,653 filed on Aug. 27, 2014, which claims the benefit of priorityunder 35 USC 119(e) of U.S. Provisional patent application Ser. No.61/871,464 filed on Aug. 29, 2013. The contents of the aboveapplications are all incorporated by reference as if fully set forthherein in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to messagingand, more specifically, but not exclusively, to methods and systems forprofiling electronic messages.

The existing infrastructure and low cost of electronic communicationshas resulted in an explosion of transmitted information. Individuals aresubject to an ever increasing volume of email, short message service(SMS), instant messaging and/or the like. For example, email users,especially those with broad interest or job scope, may receive hundredsof emails daily. A prominent example is newsletters dissemination whichis used by many companies and organizations in order to distributeinformation, for example promotional content, to large-scale audiences.These include information such as News and Advertisement. These emailare usually distributed to a very large distribution list (bulk email),using automated tools. Companies like Amazon™, Apple™, Best-Buy™ and thelike use these emails to reach a large targeted audience.

All of these messages are sorted through in order to prioritize thosecommunications that demand attention and eliminate those that have novalue to the recipient. Additionally, messages need to be cataloged,categorized, or sorted so that they can be readily accessed at a latertime. It is desirable to perform all of these tasks in an efficientmanner.

Typical solutions for handling email include viewing inbound mail bypriority; for example, by color coding inbox views based on the emailsender. Email is often analyzed based on content and manually orautomatically assigned tags, or attributes to better allow futurereference. A user may often manually examine and pigeonhole email,assigning tags, or filing the email in named folders. Storing email canalso be done by algorithm based on time, source, topic. Machine learningalgorithms can study an email user's patterns and recommend informationstorage schemes, or inbound attention priority schemes. These sufferfrom various problems, for example, not all mail from a source may havethe same connotations of urgency, topic, or importance. Manual methodsfor handling email are slow and effortful. While faster, and requiringless effort on the part of the user, automated analysis may fail whenemail correspondents are uninformed or overdramatic (e.g., when theemail is written to dramatize a situation which is not dramatic, orencourage action which is unnecessary). Additionally, machine learningcan reinforce poor patterns of information management, learning from theemail user's errors as well as her successes. Furthermore, as userscollaborate with their colleagues, it is often discovered that initialsorting, or attribute tagging may be wrong, for example, as the usercomes to better understand an evolving situation.

SUMMARY OF THE INVENTION

The present invention, in some embodiments thereof, relates to messagingand, more specifically, but not exclusively, to methods and systems forprofiling electronic messages.

According to some embodiments of the present invention, there isprovided computerized method of associating an electronic message socialprofile with electronic messages. The method comprises identifying aplurality of users having a social affinity to one another, tagging eachof a plurality of electronic messages received at a plurality ofmessaging accounts of the plurality of users with at least one userbehavior tag indicative of a behavioral messaging action performed byone of the plurality of users, identifying a cluster of electronicmessages having a common content from the plurality of electronicmessages according to a similarity analysis, calculating, using aprocessor, an electronic message social profile for members of thecluster based on a combination of respective the at least one userbehavior tag of the members of the cluster, and associating theelectronic message social profile with the members of the cluster.

Optionally, the plurality of electronic messages comprise a memberselected from a group consisting of a cellular message, an electronicmail, a broadcasted instant message (IM), and a multicasted IM.

Optionally, the common content is a common metadata value from ametadata field.

More optionally, the computerized method further comprises indicating toa first user of the plurality of users when a second user of theplurality of users is presented with a member of the cluster andestablishing in response to a user input of the first user aninteractive communication session between the first user and the seconduser.

Optionally, the social affinity is identified according to an analysisof a member selected from a group consisting of a plurality of userprofiles of the plurality of users, a plurality of web browsing logs ofthe of the plurality of users, a plurality of past correspondencesbrowsing logs of the of the plurality of users.

Optionally, the identifying a plurality of users is performed by ananalysis of content of electronic messages designated to the pluralityof users.

Optionally, the identifying a plurality of users is performed by ananalysis of a plurality of correspondences between the plurality ofusers.

Optionally, the social affinity is indicative of at least one commondemographic characteristic among plurality of users.

Optionally, the message social profile comprises a summary of aplurality of behavioral messaging actions taken by the plurality ofusers.

Optionally, the behavioral messaging action comprises opening anattachment in one of the plurality of electronic messages.

Optionally, the behavioral messaging action is a purchase of a productpromoted in the content of the plurality of electronic messages.

Optionally, the behavioral messaging action an user set rule which isautomatically applied on at least one of the plurality of electronicmessages.

Optionally, the behavioral messaging action comprises responding to oneof the plurality of electronic messages.

Optionally, the behavioral messaging action comprises deleting anunrendered of electronic message of the plurality of electronicmessages.

Optionally, the behavioral messaging action comprises adding a user tagto one of the plurality of electronic messages.

More optionally, the computerized method further comprises monitoring alocation of at least some of the plurality of users; wherein thebehavioral messaging action is identified by the monitoring; wherein thebehavioral messaging action is an arrival to an event location of eventdefined in the plurality of electronic messages.

Optionally, the social affinity is identified according to an analysisof a plurality of social connections associating between the pluralityof users in a social network.

Optionally, the plurality of electronic messages comprises a pluralityof newsletters.

More optionally, the computerized method further comprises filtering aforwarding of one of the plurality of electronic messages by one of theplurality of users to another based on the electronic message socialprofile.

Optionally, members of the cluster share at least one common electronicmessage identifier.

More optionally, the identifying a cluster comprises identifying the atleast one common electronic message identifier by textually analyzing aplurality of word strings in each one of the plurality of electronicmessages using approximate string matching algorithm.

Optionally, the identifying a cluster comprises identifying the at leastone common electronic message identifier by analyzing metadata of eachone of the plurality of electronic messages.

Optionally, the at least one common electronic message identifier isextracted from metadata of each member of the cluster.

According to some embodiments of the present invention, there isprovided a messaging system profiling electronic messages. The systemcomprises a processor, and a user interface module which instructs apresentation of a user interface by a display of a client terminal, theuser interface allows a certain user to tag with at least one user addedtag an electronic message received at an messaging account associatedwith the certain user, a social analyzer module which identifies, usingthe processor, a users group comprising a plurality of users having asocial affinity to the certain user, a profiling module which matchesbetween the electronic message and an additional electronic messagereceived at another messaging account associated with another user; anda additional user interface module which instructs the presentation ofthe at least one user added tag in association with the presentation ofthe additional electronic message to the another user using anadditional client terminal.

According to some embodiments of the present invention, there isprovided computerized method of associating an electronic message socialprofile with electronic messages. The method comprises identifying ausers group comprising a plurality of users having a social affinity toone another, identifying a plurality of electronic messages sharing atleast one common electronic message identifier, each one of theplurality of electronic messages is sent to another of the plurality ofusers, calculating, using a processor, an electronic message socialprofile for each one of the plurality of electronic messages, andassociating the electronic message social profile with respectiveelectronic message of the plurality of electronic messages.

According to some embodiments of the present invention, there isprovided computerized method of tagging an electronic message for socialprofiling. The method comprises simultaneously presenting to a user, ona display of a client terminal and in association with one another, auser interface and a content of an electronic message, inputting by auser who uses the user interface a content quality indicative tag,identifying a plurality of users having a social affinity to the userand received a plurality of electronic messages with the content,calculating, using a processor, an electronic message social profile forthe plurality of electronic messages based on the content qualityindicative tag, and presenting an indication of the content qualityindicative tag to the plurality of users.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention.

In this regard, the description taken with the drawings makes apparentto those skilled in the art how embodiments of the invention may bepracticed.

In the drawings:

FIG. 1 is a flowchart of a method of socially profiling and taggingelectronic messages based on behavioral messaging action(s) performed byone or socially affiliated users, according to some embodiments of thepresent invention;

FIG. 2 is a schematic illustration a system for socially profiling andoptionally tagging electronic messages, for instance by implementing themethod depicted in FIG. 1, according to some embodiments of the presentinvention; and

FIG. 3 is an exemplary screenshot of content of an electronic message,according to some embodiments of the present invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to messagingand, more specifically, but not exclusively, to methods and systems forprofiling electronic messages.

According to some embodiments of the present invention, there areprovided methods and systems of profiling electronic messages havingcommon media content based on behavioral messaging action(s) of usersreceiving the electronic messages with the common media content,according to some embodiments of the present invention.

Optionally, a plurality of electronic messages accounts are monitored inreal time to identify and cluster electronic messages having the commonmedia content, for instance similar or identical text, links, videoand/or audio content. The clustering may be performed by media contentidentifiers, metadata identifiers, and/or the like. By analyzing andidentifying social affiliation among recipients of the electronicmessages, a group of socially affiliated users who received the samemedia content is identified. The methods and systems allow presenting toa recipient of one of these electronic messages, a social profileindicative of behavioral messaging action(s) performed by other usersregarding and/or in response to the media content. Additionally oralternatively, the methods and systems allow managing actions related tothe electronic messages according to behavioral messaging action(s)performed by other users. The actions may be, for example, filteringelectronic messages, forwarding electronic messages, replying toelectronic messages, sorting electronic messages, ignoring electronicmessages, deleting electronic messages, and/or the like.

Optionally, an infrastructure that allows recipients of the aboveelectronic messages to communicate, for example via a chat, feedbackpublication or call, is provided.

According to some embodiments of the present invention, there areprovided methods and systems of providing users with a tool, a userinterface, for tagging media content in an electronic message theyreceived, having their socially affiliated users, for example friends ina social network, gain value from the time they invested reviewing themedia content. The tagging may indicate to socially connected users thatthe media content should be positively or negatively considered. Thetagging may include a personal impression of the tagging user.

According to some embodiments of the present invention, there areprovided methods and systems managing electronic messages traffic amongor from socially affiliated users based on behavioral messagingaction(s) they perform. The traffic may be managed before sortingelectronic messages into folders, for example before an electronicmessage is added to an inbox. The traffic may be managed after theelectronic messages are received, for example by implanting forwardingand/or replying rules.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Reference is now made to FIG. 1, which is a flowchart 100 of a method ofsocially profiling and optionally tagging electronic messages designatedto users based on behavioral messaging action(s) performed by one ormore other users which are socially affiliated therewith, according tosome embodiments of the present invention. As used herein, an electronicmessage may be an electronic mail (email), an instant message, acellular message, such as an short message service (SMS) or anmultimedia messaging service (MMS), an instant message (IM), abroadcasted or multicasted media message, such as a broadcasted ormulticasted text message, a broadcasted or multicasted video messageand/or a broadcasted or multicasted audio message. As used herein, abehavioral messaging action is any user performed action such as openingelectronic message, forwarding an electronic message, responding to anelectronic message, viewing attachment(s) of an electronic message,categorizing an electronic message, blocking a recipient of anelectronic message, deleting an electronic message, marking anelectronic message, flagging or labeling an electronic message, movingan electronic message to a certain folder, for instance archiving,writing a response to an electronic message, ignoring an electronicmessage, for instance by bit opening them for elaborated presentation,the time spent on an electronic message, the number of times anelectronic message was opened, which device was used to open theelectronic message, browsing to link in an electronic message, searchingfor an electronic message, following an electronic message and/or thelike.

Reference is also made to FIG. 2, which is a schematic illustration asystem 200 for socially profiling and optionally tagging electronicmessages, for instance by implementing the method depicted in FIG. 1,according to some embodiments of the present invention. The system 200includes a processor based network node, such as one or more servers201. The one or more servers 201 includes one or more computerizedprocessor(s) 202, such as central processor unit(s), and a profilingmodule 203 that socially profiles and optionally tags electronicmessages, for instance as described below. The system 200 furtherincludes one or more user interface modules. The user interface modulesmay be locally managed by the one or more servers 201, for instance asdepicted by numeral 204. Such user interface modules 204 may be modulesgenerating user interfaces, such as graphical user interfaces (GUIs)which are rendered by browsers installed in one or more client terminals206, such as laptops, desktops, Smartphones, tablets, smart glasses,and/or any other user controlled computing unit. As depicted by numeral207, the user interface modules may be installed in the client terminals206 themselves, for instance as applications, browser add-ons, an e-mailinformation management software product add on and/or the like. Thesystem 200 optionally includes one or more repositories for storingelectronic messages clustering information and/or electronic messagestagging data, for instance as described below. Optionally, the profilingmodule 203 includes or uses application program interface (API)module(s) for interfacing with third party systems taking advantage ofthe electronic message profiling.

As depicted in 101, different messaging accounts of a plurality ofdifferent electronic message recipients, also referred to herein asusers or recipients, are monitored. The messaging accounts may be anyelectronic messages account, such as mail accounts and IM accounts. Theelectronic message recipients are optionally subscribers of the system200 and/or subscribers of messaging supported system or network, forinstance social network peers, such as Facebook™ peers or Twitter™ peersand/or messaging service users, such as WhatsApp™ subscribers and/orLine™ subscribers.

For example, multiple email accounts are monitored by executing onlineprocessing agent(s). The processing agents scan and analyze the receivedemails in each monitored account. In such embodiments, an indicationabout new emails may be received by an email server, such as internetmessage access protocol (IMAP) IDLE protocol server (see RFC 2177 whichis incorporated herein by reference). The new emails may be fetched andscanned by the profiling module 203. Optionally, the emails are receivedfrom the email server via a push mechanism, and then be scanned by theprofiling module 203. Optionally, the emails are received from the emailserver by periodic fetch, for example every minute, 5 minutes, 10minutes, 1 hour and/or any intermediate or longer period.

This allows, as shown at 102, analyzing the similarly between electronicmessages sent to the different messaging accounts. In such a manner,electronic messages without any substantial content differences areclustered, for example electronic messages with an addressee/recipientdifference, a sender difference, a name difference, a title difference,a transmission, time difference, a personal promotional contentdifference, a language difference, and/or an address difference, and/ora legality section difference. As used herein, content may includetextual, visual and/or audible content that is sent in an electronicmessage. For example, FIG. 3 depicts content, promotional content of anewsletter from Amazon™. Personal attributes of the electronic messageare omitted, for instance email address and links; however, promotionaloffers remain as part of the content. In this example, the content hasthe common features in different electronic messages which are sent todifferent recipients, for example links, textual content, structure, andimages.

The electronic messages may be originated from any source, for examplean organization, such as the working place of the recipient, businessentities, commercial entities such as insurance company, a car dealer, autility company, a tourists attraction, a financial advisor, bank, arestaurant, bookmakers or handymen services, leisure or hobbies centerthe recipient is or is not a member of, physical social groups therecipient belongs to (for instance a book club, a museum, a gym) andspecial interests group (for instance a religious community, or parentsto kids with special needs). The electronic message may be a newsletter.The newsletter may be sent to a user as an outcome of being registeredto in a distribution list and/or any entity regardless of the user beingregistered.

The similarity analysis of each electronic message is based oncharacteristics of media content it contains and/or the metadatathereof. The analysis is optionally a similarity analysis that is set toidentify similar or identical media content or metadata of differentelectronic messages. As used herein, media content includes text, links,video and/or audio content that is sent for presentation (visual,audible) by one or more human recipients. In the similarity analysis oneor more common electronic message identifiers are identified. Theelectronic message identifiers, may be textual features (e.g. similar oridentical text), media content features (e.g. similar or identical audioand/or video files), metadata features (e.g. similar or identicalmetadata fields, such as identifiers, for instance (e.g. Message-IDaccording to request for comments (RFC)5322 standard), structuralfeatures (e.g. an arrangement of visual components, such as text boxesand images in the electronic message), electronic message sender data,and/or electronic message size features. The similarity analysis, mayinclude, for example, one or more of the following:

-   -   Text matching—for example matching of words, sentences and/or        paragraphs among the electronic messages. The text matching is        optionally based on textually analyzing a plurality of word        strings in each one of the electronic messages using approximate        string matching algorithm. For example, binary comparison of the        electronic messages may be established by calculating a        similarity to change ratio and using a ratio threshold.        Optionally, only selected part(s) of an electronic message is        analyzed. The part(s) may be selected based on learning modules.    -   Temporal analysis—for example matching of time of receipt, the        time of delivery and/or any other time tag, for instance from        the metadata of the electronic messages.    -   Structural analysis—for example matching arrangements of        hypertext markup language (HTML) components, and/or the like.    -   Origin analysis—for example matching the direct sender and/or        original sender of electronic messages, for example who is the        sender which has originally sent a forwarded electronic message.    -   Size analysis—for example matching the file size of the        electronic messages.    -   Metadata analysis—for example matching metadata fields among the        electronic messages, for instance matching electronic message        identifiers. For example, metadata fields, also referred to as        identifiers, from an email may be fields of an email header        and/or an email schema, and/or the other meta information such        as the size, or MD5 hash. Such analysis does not require a full        content inspection.

When the electronic messages include emails, the profiling module maycompare monitored emails to identify emails which are essentiallyreplications of one another. Optionally, the analysis may be optimizedto similar messages and then a brute force may fine tune the analysis.

Optionally, promotional or advertisement content is identified andfiltered out such that only the rest of the media content an electronicmessage contains is analyzed and optionally matched.

Optionally, a dynamic feedback user interface may be generated to allowa user to optimize parameters and settings to adjust similaritydetection and avoid false negative detection, when similar emails arenot detected, and/or false positive detection, when non similar emailsare not detected.

As shown at 103, based on the analysis, similar or identical electronicmessages received at the monitored messaging accounts are identified andoptionally clustered, for example electronic messages subsets, alsoreferred to herein as electronic message clusters, for brevity referredto herein as clusters. The clusters are optionally stored in arepository, such as 209. Each cluster represents unique media contentcommonly found in the electronic messages of the cluster, for examplepromotional content, community content, malicious content and/or thelike. The content may be newsletter media content, advertisement, socialnetwork message and/or the like.

As shown at 104, groups of socially affiliated recipients areidentified. Each socially affiliated recipients group includesreferences of users, namely monitored recipients of electronic messages,having a social affinity to one another.

The socially affiliated recipients group may be identified by analyzingsocial connections between the users, for instance friendshiprelationship in a social network such as Facebook™ or work relationshipin a business network such as Linkedin™.

An exemplary socially affiliated recipients group is a group of usersconnected to one another by a first degree, a second degree, and/or athird degree friendship relationship and/or connected by more than onefriendship relationship connection, for instance more than 2, 3, 6, 12or any intermediate or higher number of friendship relationshipconnections. Additionally or alternatively, the social affinity isidentified by an analysis of phonebooks or contact lists of the users.Additionally or alternatively, the social affinity is identified by ananalysis of addressees of electronic emails sent by or received from theusers, for instance identifying users who exchanged emails in the past.Additionally or alternatively, the social affinity is determined by ananalysis of the participation of users in common or related event (e.g.festival, conference, and concert). Additionally or alternatively, thesocial affinity is determined by an analysis of the membership of usersin common organizations. Additionally or alternatively, the socialaffinity is determined by a combination of any of the above examples,for instance in a weighted manner.

Additionally or alternatively, the social affinity is determined by ananalysis of user profiles of the plurality of users, for exampledemographic characteristics of the users, such as age, gender, a newlymarried, a new parenting, a graduation status, an employment status(looking for first job, retiring soon), economic state, alumni,geographical origin, marital status, education level and/or the likeand/or preferences such as a similar perceived interests, hobbies,activities (i.e. culture or art), community and/or the like. The userprofiles may be used to identify people enlisted to the same gym, buyersof the same products (e.g. Apple buyers), follow the same sporting team,attend a common event (e.g. same festival, conference, and/or the like).

The user profiles may be created automatically, for instance from ananalysis of electronic messages, an analysis of social webpage(s), webcrawling and/or the like. The user profiles may be created manually, forexample when the user is registered to a service. Additionally oralternatively, the social affinity is determined by web browsing logs ofthe users, for example identifying similar regions of interest.Additionally or alternatively, the social affinity is determined byanalysis of electronic messages from the accounts of the users, forexample identifying similar regions of interest. Additionally oralternatively, the social affinity is determined based on physicalproximity, for example people within 1 mile radius.

Socially affiliated recipients groups may be identified separately fromthe identification of clusters, before the identification of clusters,for instance where clusters are identified only among electronicmessages from accounts of members of a certain socially affiliatedrecipients group, and/or after the identification of clusters, sociallyaffiliated recipients groups are identified per cluster.

As shown at 105, each cluster is divided to a plurality of clustersegments according to social affiliation of the recipients of theelectronic messages. Each cluster segment includes electronic messagesfrom accounts of recipients of a common socially affiliated recipientsgroup. For example each cluster segment includes electronic messageshaving a common unique media content, such as a newsletter mediacontent, which is received by a plurality of socially connected Facebookfriends.

As shown at 106, each of some or all of the electronic messages at thedifferent messaging accounts is tagged based on behavioral messagingaction(s) which are performed by its recipient. Optionally, eachbehavioral messaging action is logged and time tagged. The tagging witha user behavior tag is indicative of a behavioral messaging action, forexample as defined above, may be performed manually by one of the users(recipients), for example the owner of the respective account, forexample using user interface modules 204, 207. For instance, a user maytag an electronic message with a Like tag, a spam tag, an ignore tag, ascore, and/or the like. The tagging with a user behavior tag may beperformed automatically, for example by the user interface modules 204,207. For example, the user interface module 204 measures the time theuser spent reviewing an electronic message and automatically tags theelectronic message positively or negatively accordingly. In anotherexample, the user interface module 204, 207 identifies a deletionwithout reading of an electronic message and automatically tags theelectronic message negatively accordingly. In another example, the userinterface module 204 identifies an electronic message which has not beenfully downloaded, for example downloaded without images, andautomatically tags the electronic message negatively accordingly.

In another example, the user interface module 204 identifies aforwarding without reading of an electronic message and automaticallytags the electronic message positively accordingly.

According to some embodiments of the present invention, the behavioralmessaging action(s) are user actions motivated by the electronic messageand performed independently from the presentation of the electronicmessage of its media content. For example, the behavioral messagingaction(s) may be a purchase of a product promoted in an electronicmessage, such as using a promotion code or a coupon. For example, thebehavioral messaging action(s) may be an arrival of a user to an eventor a retailer shop described in the electronic message optionally at thetime described in the electronic message, an access to a website orwebpage mentioned in described in the electronic message, an orderperformed in a website or webpage mentioned in described in theelectronic message, and/or the like. For example, the location of a useris monitored to identify a match or a mismatch with locations describedin the media content of electronic message to identify a behavioralresponse to the media content.

According to some embodiments of the present invention, the behavioralmessaging action(s) are user set rules, for example automaticforwarding, automatic folder selection, automatic deletion and/or thelike. In such embodiments, automatic deletion may be indicative of anegative behavioral messaging action and an automatic forwarding toother recipients and/or a folder marked as urgent or VIP may beindicative of a positive behavioral messaging action. Additionally oralternatively, behavioral messaging action(s) on a certain electronicmessage may be weighted in light of user set rules which are applied onthe certain electronic message.

As shown at 107, each cluster segment is profiled based on the tags ofthe electronic messages it contains. As used herein, containment of acluster includes any association between a cluster and a groupingidentifier, for instance a list or a reference such as a link. Forexample, the profiling module 203 calculates an electronic messagesocial profile for some or all of the electronic messages of a certaincluster segment based on a combination of user behavior tags of membersof electronic messages from the certain cluster segment.

Optionally, the calculated electronic message social profile isassociated with any message in the certain cluster segment and/or anyelectronic message added to the certain cluster segment. For example,when a member of a certain socially affiliated recipients group receivesan electronic message identified as related to a cluster segment dividedfrom a respective cluster for the certain socially affiliated recipientsgroup, the electronic message is profiled as other electronic messagesin the socially affiliated recipients group.

For example, the social profile may be presented in association with theelectronic message. For instance, the presented notification includesthe notification “5 of your friends opened an attachment and viewed avideo in this email” and/or “3 of your friends forwarded this email”.Any other action related to the media content of the electronic messagemay also be specified, for example list of indirect actions resultedfrom the electronic message (e.g. the number and/or identity of userswho used a coupon received in the electronic message, the number and/oridentity of users who made a purchase of a product and/or participatedin an event advertised in the electronic message, the number and/oridentity of users who downloaded an application advertised in theelectronic message.

Optionally, the social profile includes a score, a rank, and/or a statuscalculated based on the recorded tags. For example, the social profileincludes a color on a scale reflecting user's perception about the mediacontent, for example red reflects malicious or boring and green reflectssafe or interesting.

Optionally, the social profile includes a summary of a plurality ofbehavioral messaging actions taken by respective users, for example thenumber of Like tags, for example the number of dislike tags, an averageviewing time, a time to deletion, ratio between the number of users whodeleted without reading and the number of users who deleted afterreading, and/or the like.

According to some embodiments of the present invention, the socialprofile of an electronic message, namely the social profile of thecluster segment to which it belongs, is presented to a viewer of theelectronic message, for instance by a browser or a messaging and/orpersonal information management software. Optionally, the social profileis rendered by a browser add on. Optionally, the social profile isrendered by a browser toolbar. Optionally, the social profile isrendered as an overlay on top of a presentation of the electronicmessage. Optionally, the social profile is rendered as an overlay on topof a presentation of the electronic message.

As shown at 95, 96, the electronic message accounts and the socialaffiliation among the users is continuously monitored, allows updatingthe cluster segments and their social profiling continually, for exampleiteratively.

According to some embodiments of the present inventions, the system 200allows a recipient watching an electronic message from a certain clusteror cluster segment to establish a communication session with one or moreother recipients of an electronic message from the same cluster orcluster segment, for example users of a socially affiliated recipientsgroup to which she belongs. The communication session may be a chat, anIM session, Optionally, session is established by a GUI that ispresented in association with the electronic message, for example a GUIindicating which of the other users is currently reviewing an electronicmessage from the same cluster or cluster segment, namely with the sameor similar media content. Optionally, the GUI present indications ofwhich of the users is currently reviewing these electronic messages, forinstance using online, offline, and busy signs. In such a manner, userswatching the same media content, for example a newsletter maycommunicate to exchange opinion thereabout. Optionally, a transcript ofthe communication session is created and logged. Such a transcript is abehavioral messaging action which may be monitored and analyzed toautomatically generate respective user behavior tags. For example, thetranscript may be semantically and/or contextually analyzed to identifypositive or negative reaction to the media content.

According to some embodiments of the present inventions, the system 200allows a recipient watching an electronic message from a certain clusteror cluster segment to leave remarks, comments, to one or more otherrecipients of an electronic message from the same cluster or clustersegment, for example users of a socially affiliated recipients group towhich she belongs. This allows the user to leave a personal notepertaining to the media content. The remarks and/or comments arebehavioral messaging action(s) which may be monitored and analyzed toautomatically generate respective user behavior tags. For example, theremarks and/or comments may be semantically and/or contextually analyzedto identify positive or negative reaction to the media content.

According to some embodiments of the present inventions, the system 200manages the transmission of electronic messages based on their socialprofile, for instance controls or adjusts the forwarding and/or replypattern of electronic messages based on their social profiles. Forexample, a forwarding of an electronic message may be moderated bypresenting to the sending user a notification emphasizing the socialprofile of the electronic message, for example presenting a notificationasking a user to confirm a forwarding of the electronic message to afriend even though the electronic message was tagged with a socialprofile:“spam”, “dislike”, and/or “waste of time”. In another example,when deleting an unopened message that others have spent time reading,in yet another example, a calendar invitation that many others acceptedis declined.

According to some embodiments of the present inventions, the system 200performs socially related actions including automatic forwarding of themedia content in electronic messages of a certain cluster segment tomembers of a respective socially affiliated recipients group based onthe analysis of the recipients in the certain bucket. For instance, ifthe media content is an event related media content including aninvitation to an event, the analysis of the recipients in the certainbucket may be used to automatically identify socially connected userswho did not receive the event related media content. In another example,the socially related actions depend on the reaction of the recipients ofelectronic messages in a certain cluster segment to the media content ofthe electronic messages. For instance, when a positive reaction topromotional media content is identified based on the analysis ofsocially related actions the promotional media content is forwarded toother members of a respective socially affiliated recipients group.

According to some embodiments of the present inventions, social profilesof electronic messages are used for dynamic filtering thereof. In suchembodiments, an electronic message that is about to be added to anincoming account is matched with a cluster segment, for instance asdescribed above, and profiled accordingly with a social profile. Basedon the social profile the received electronic message is stored in aninbox, stored in a junk mail inbox, automatically deleted, automaticallytagged and/or the like. Optionally, a tag indicative of the socialprofile is added to the title of an electronic massage. Additionally oralternatively, a tag indicative of the social profile is added to themetadata of an electronic massage. Additionally or alternatively, a tagindicative of the social profile is added to the text of the mediacontent of an electronic massage. This allows filtering of an electronicmessage using existing filtering methods and systems.

According to some embodiments of the present inventions, social profilesof one recipient of electronic messages clustered in a cluster segmentare updated or calculated based on the social profiles of recipients ofelectronic messages clustered in the cluster segment. For example,differences between social profiles of these recipients are identifiedand used to create a social profile for each recipient or for a newrecipient. In such embodiments, when an electronic message, such as anewsletter is received, a social profile to one or more of itsrecipients is created based on the characteristics of recipients whichare socially affiliated thereto.

Reference is now made to exemplary profiling of an electronic message, anewsletter, according to some embodiments of the present invention. Forexample, electronic messages, emails, including a newsletter received byvarious recipients from Amazon(dot)com differ in time, recipient addressand unsubscribe links; however, this electronic messages share the exactpromotional media content including headers fields such as the “fromaddress”. The system 200, for example using the profiling module 203,monitors email accounts of users and maps them, holding a pointer to allinstances of the same newsletter. Once such mapping is establishedfunctionalities are offered as described above.

The methods as described above are used in the fabrication of integratedcircuit chips.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

It is expected that during the life of a patent maturing from thisapplication many relevant methods and systems will be developed and thescope of the term a unit, a module, a network, and a server is intendedto include all such new technologies a priori.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”. This termencompasses the terms “consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments and/or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting. In addition, any priority document(s) of this applicationis/are hereby incorporated herein by reference in its/their entirety.

What is claimed is:
 1. A computerized method of associating anelectronic message social profile with electronic messages, comprising:identifying a plurality of users having a social affinity to oneanother; tagging each of a plurality of electronic messages received ata plurality of messaging accounts of said plurality of users with atleast one user behavior tag indicative of a behavioral messaging actionperformed by one of said plurality of users; identifying a cluster ofelectronic messages having a common content from said plurality ofelectronic messages according to a similarity analysis; calculating,using a processor, an electronic message social profile for members ofsaid cluster based on a combination of respective said at least one userbehavior tag of said members of said cluster; and associating saidelectronic message social profile with said members of said cluster. 2.The computerized method of claim 1, wherein said plurality of electronicmessages comprise a member selected from a group consisting of acellular message, an electronic mail, a broadcasted instant message(IM), and a multicasted IM.
 3. The computerized method of claim 1,wherein said common content is a common metadata value from a metadatafield.
 4. The computerized method of claim 1, further comprisingindicating to a first user of said plurality of users when a second userof said plurality of users is presented with a member of said clusterand establishing in response to a user input of said first user aninteractive communication session between said first user and saidsecond user.
 5. The computerized method of claim 1, wherein said socialaffinity is identified according to an analysis of a member selectedfrom a group consisting of a plurality of user profiles of saidplurality of users, a plurality of web browsing logs of said of saidplurality of users, a plurality of past correspondences browsing logs ofsaid of said plurality of users.
 6. The computerized method of claim 1,wherein said identifying a plurality of users is performed by ananalysis of content of electronic messages designated to said pluralityof users.
 7. The computerized method of claim 1, wherein saididentifying a plurality of users is performed by an analysis of aplurality of correspondences between said plurality of users.
 8. Thecomputerized method of claim 1, wherein said social affinity isindicative of at least one common demographic characteristic amongplurality of users.
 9. The computerized method of claim 1, wherein saidmessage social profile comprises a summary of a plurality of behavioralmessaging actions taken by said plurality of users.
 10. The computerizedmethod of claim 1, wherein said behavioral messaging action comprisesopening an attachment in one of said plurality of electronic messages.11. The computerized method of claim 1, wherein said behavioralmessaging action is a purchase of a product promoted in the content ofsaid plurality of electronic messages.
 12. The computerized method ofclaim 1, wherein said behavioral messaging action an user set rule whichis automatically applied on at least one of said plurality of electronicmessages.
 13. The computerized method of claim 1, wherein saidbehavioral messaging action comprises responding to one of saidplurality of electronic messages.
 14. The computerized method of claim1, wherein said behavioral messaging action comprises deleting anunrendered of electronic message of said plurality of electronicmessages.
 15. The computerized method of claim 1, wherein saidbehavioral messaging action comprises adding a user tag to one of saidplurality of electronic messages.
 16. The computerized method of claim1, further comprising monitoring a location of at least some of saidplurality of users; wherein said behavioral messaging action isidentified by said monitoring; wherein said behavioral messaging actionis an arrival to an event location of event defined in said plurality ofelectronic messages.
 17. The computerized method of claim 1, whereinsaid social affinity is identified according to an analysis of aplurality of social connections associating between said plurality ofusers in a social network.
 18. The computerized method of claim 1,wherein said plurality of electronic messages comprises a plurality ofnewsletters.
 19. The computerized method of claim 1, further comprisingfiltering a forwarding of one of said plurality of electronic messagesby one of said plurality of users to another based on said electronicmessage social profile.
 20. The computerized method of claim 1, whereinmembers of said cluster share at least one common electronic messageidentifier.